Blockchain Needs to Lay the Foundation for a Transparent and Trustworthy AI Ecosystem

As artificial intelligence (AI) systems have become increasingly more complex and influential since the turn of the last decade, there has been a growing need to ensure that these systems are not only powerful but also transparent, accountable, and trustworthy.

In this regard, a recent survey by McKinsey Global found that 72% of all organizations today are using AI, a notable increase from previous years. Not only that, 65% of the respondents reported regularly using generative AI in at least one business function, doubling adoption rates since 2023.

Similarly, another report showed that 77% of all individuals now use AI globally, thus showcasing their growing familiarity with and reliance on AI technologies in everyday life. Thus, in the wake of these developments, it is essential to forge a transparency-driven AI economy that allows users to operate freely without worrying about their private info being misused.

This is where blockchain tech stands to be a game-changer, offering a robust infrastructure that can pave the way for more trustworthy AI projects, especially those operating across critical domains such as healthcare, finance, and public safety. 

With its fundamental properties of immutability and decentralization, the blockchain provides a promising foundation of unalterable records when large language models (LLMs) are being trained. This includes the optimization of their data sets, applied algorithms, and bias training modules (among other aspects).

Furthermore, by leveraging these decentralized ledgers (DLTs), it is possible to create tamper-proof audit trails, allowing for unprecedented levels of verification and accountability. Not only that, by recording each input, decision-making process, and output, it is possible to ensure tamper-free AI operations.

Safeguarding Humanity’s Critical Systems

The implications of combining blockchain and AI extend far beyond transparency, as their synergy can revolutionize how we certify and trust AI models in human-critical tasks — especially in industries such as aviation, healthcare, and critical infrastructure management.

Imagine an AI system controlling air traffic or assisting in complex surgical procedures. The stakes are incredibly high, and any error can have catastrophic consequences. By utilizing the blockchain to record and verify every aspect of an AI platform – from their training to their decision-making processes – it is possible to establish an unparalleled level of accountability and trust.

Projects like 0G are doing just this by pioneering a scalable data availability system that integrates seamlessly with blockchain tech. The infrastructure is designed to handle the massive amounts of data required for AI model training and operation while maintaining utmost transparency and immutability.

0G’s approach is particularly noteworthy because it addresses one of the key challenges in merging AI and blockchain: scalability. Traditional blockchain systems often struggle with the high-volume, high-velocity data requirements of modern AI systems. 0G’s innovative architecture, however, allows for the horizontal scaling of nodes, enabling it to process data at rates up to 50 gigabytes (GB) per second – a speed that is orders of magnitude faster than many competitors in the space.

Furthermore, by offering features like programmable data availability and dedicated consensus layers for specific customers, 0G is building a flexible, secure foundation upon which transparent and accountable AI systems can be developed.

The potential applications are vast. From ensuring the integrity of AI-driven financial models to providing verifiable proof of fairness in AI-powered hiring systems, 0G’s infrastructure has the potential to set new standards for AI trustworthiness across industries.

Addressing public concerns

The need for transparent AI systems is fast being highlighted by growing public skepticism. Recent studies have revealed a significant trust gap between AI developers and the general public, with 60+% of the respondents noting that today’s AI offerings lack transparency.

This skepticism isn’t limited to the general public. Even in the business world, where AI adoption is often seen as a competitive advantage, there’s a clear demand for more transparent AI practices. A recent survey found that while 90% of business executives believe transparency is crucial for building customer trust, only 30% of consumers feel that companies are sufficiently transparent about their AI systems.

Despite these startling numbers, efforts to achieve this transparency remain pretty poor. A study found that transparency scores associated with today’s AI systems range between 6.4% to 60.9% —  with a median score of just 29.1% — suggesting key gaps in their documentation and transparency.

Thus, looking ahead, projects like 0G seem to be leading the way in creating the necessary infrastructure to support this integration, addressing key challenges like scalability and data management along the way.